期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2010
卷号：XXXVIII - Part 1
出版社：Copernicus Publications
摘要：This paper presents a method for retrieval of remote sensing images using low dimensional code of the spatial layout of a scene,which is proposed to represent the meaning of the scene. This semantic feature is based on the statistical features of gradientorientations. To capture coarse spatial information, the semantic feature is represented in a pyramidal structure. The level of thepyramid structure is evaluated in this paper for the remote sensing image retrieval tasks. Many features are proposed to describe thesemantic information of the images, however, the scale of the measurement of them are no or less discussed in these researches.There are three candidates of measurement scale for image retrieval task: the interval scale, ordinal scale, and ratio scale. To evaluatethe three measurement scales of semantic features for remote sensing image retrieval, this paper build a remote sensing image dataset,which is composed of ten image categories: Olympic gymnasium, urban area, campus of university, island, navy base, aircraft carrier,nuclear reactor, air base, cloverleaf junction, and mountain peak. The average normalized modified retrieval rank (ANMRR) areused to estimate the performance of semantic features with different measurement scales for remote sensing image retrieval task onour dataset. These experimental results demonstrate that ordinal scale is more effective for image retrieval task.
